一、方法的陈述自从本世纪三十年代 ARMA 混合模式问世以来,在时间序列分析和预测中,它日益成为一种重要而经常使用的手段。和时间序列其他预测方法相比较,这种方法具有相当的灵活性和优越性。它不仅可以拟合各种不同的数据样式,通过若...一、方法的陈述自从本世纪三十年代 ARMA 混合模式问世以来,在时间序列分析和预测中,它日益成为一种重要而经常使用的手段。和时间序列其他预测方法相比较,这种方法具有相当的灵活性和优越性。它不仅可以拟合各种不同的数据样式,通过若干次迭代获得最佳参数估计值;展开更多
24-26 February,2016,Rome,Italy The International Conference on Pattern Recognition Applications and Methods would like to become a major point of contact between researchers,engineers and practitioners on the areas of...24-26 February,2016,Rome,Italy The International Conference on Pattern Recognition Applications and Methods would like to become a major point of contact between researchers,engineers and practitioners on the areas of Pattern Recognition,both from theoretical and application perspectives.Contributions describing applications of Pattern Recognition techniques to real-world problems,interdisciplinary research,experimental and/or theoretical studies yielding new insights that advance Pattern Recognition methods are especially encouraged.展开更多
提出一种基于鲁棒最小二乘支持向量机(LS-SVM)的控制图模式识别方法,并研究其应用于过程质量诊断的可行性、有效性.理论研究和仿真试验结果表明,该方法对于标准的6种控制图模式都具有很高的模式识别率,训练模式识别器所需样本少,且训练...提出一种基于鲁棒最小二乘支持向量机(LS-SVM)的控制图模式识别方法,并研究其应用于过程质量诊断的可行性、有效性.理论研究和仿真试验结果表明,该方法对于标准的6种控制图模式都具有很高的模式识别率,训练模式识别器所需样本少,且训练结果泛化能力强,计算方法简单迅速.
Abstract：
A technique based on the robust least squares support vector machines(LS-SVM) used for control charts pattern recognition is proposed, the applied feasibility and validity of this technique in process quality diagnosis is also investigated. Theoretical research and experimental results show that this approach performs well upon the six typical control charts pattern recognition with high recognition accuracy, simple computation and fast training process, and the preeminent generalization ability on the condition of small sample size.展开更多
文摘24-26 February,2016,Rome,Italy The International Conference on Pattern Recognition Applications and Methods would like to become a major point of contact between researchers,engineers and practitioners on the areas of Pattern Recognition,both from theoretical and application perspectives.Contributions describing applications of Pattern Recognition techniques to real-world problems,interdisciplinary research,experimental and/or theoretical studies yielding new insights that advance Pattern Recognition methods are especially encouraged.
文摘提出一种基于鲁棒最小二乘支持向量机(LS-SVM)的控制图模式识别方法,并研究其应用于过程质量诊断的可行性、有效性.理论研究和仿真试验结果表明,该方法对于标准的6种控制图模式都具有很高的模式识别率,训练模式识别器所需样本少,且训练结果泛化能力强,计算方法简单迅速.
Abstract：
A technique based on the robust least squares support vector machines(LS-SVM) used for control charts pattern recognition is proposed, the applied feasibility and validity of this technique in process quality diagnosis is also investigated. Theoretical research and experimental results show that this approach performs well upon the six typical control charts pattern recognition with high recognition accuracy, simple computation and fast training process, and the preeminent generalization ability on the condition of small sample size.
